According to a current international video coding standard, such as H.264 or MPEG-4, a video signal is hierarchically divided into a sequence, a frame, a slice, a macroblock, and a block, wherein the block is a minimum processing unit. With respect to encoding, a prediction remaining error of the block is determined via intra-frame or inter-frame prediction, block transformation is performed such that energy is focused on a coefficient of a decimal, and image data is compressed and recorded as a coded bitstream via quantization, scanning, run-length coding, and entropy coding. With respect to decoding, processes are performed in the opposite order. First, a block transformation coefficient of entropy coding is extracted from a bitstream. Then, a prediction remaining error of a block is reconstructed via inverse-quantization and inverse-transformation, and prediction information is used to reconstruct video data of the block. In an encoding-decoding process, a transformation module is a base of video compression, and transformation performance of the transformation module directly affects the general performance of a codec.
Discrete cosine transform (DCT) has been employed in conjunction with an initial video coding standard, such as MPEG-1 or H.261. After DCT was introduced in 1974, DCT has been widely used in image and video coding fields. Transformation performance of DCT is excellent compared to all sub-optimal transforms, because DCT removes a correlation of image elements in a transformation domain and prepares a base for highly-efficient image compression. However, because a DCT matrix is expressed using floating point numbers, many system resources are used due to massive floating point operations. Accordingly, a new DCT algorithm is required so as to improve transformation efficiency while performing transformation on a large-size block.